La diabetes mellitus tipo 1 es una enfermedad crónica que afecta aproximadamente a 30 millones de personas en el mundo y se caracteriza por niveles de concentración de glucosa en sangre elevados producidos por una deficiencia absoluta de insulina. Ello produce numerosas complicaciones a largo plazo como retinopatía, nefropatía y neuropatía entre otras. Las terapias actuales basadas en el suministro de insulina exógena (por inyecciones o bomba de insulina), no consiguen normalizar los niveles de glucosa de forma eficiente. Los avances tecnológicos en la última década en sistemas de medición continua de glucosa e infusión de insulina, han impulsado el desarrollo del páncreas artificial, o control automático de infusión de insulina. En este trabajo se presentará, a modo de tutorial, el pasado, presente y futuro de esta tecnología, tan esperada por el paciente diabético. Se revisará el estado actual de la tecnología para la sensorización y actuación, principales desafíos desde el punto de vista de control, las diferentes “escuelas” y estudios clínicos del desempeño de controladores, así como herramientas de validación de controladores mediante simulación. Dada la complejidad del problema, el desarrollo del páncreas artificial será de forma escalonada, redundando progresivamente en la mejora de la calidad de vida del paciente. Los grandes avances en los últimos cinco años hacen preveer un horizonte cercano para la primera generacioń de pańcreas artificial.
Información de la revista
Vol. 7. Núm. 2.
Páginas 5-20 (abril 2010)
Vol. 7. Núm. 2.
Páginas 5-20 (abril 2010)
Open Access
El Páncreas Artificial: Control Automático de Infusión de Insulina en Diabetes Mellitus Tipo 1
Visitas
5974
* Instituto Universitario de Automática e Informática Industrial, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia, España
** Institut d'Informática i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071 Girona, España
*** Medtronic Diabetes, 18000 Devonshire Street, Northridge, CA 91325-1219, U.S
**** Institute of Biomedical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K
Este artículo ha recibido
Información del artículo
Resumen
Palabras Clave:
Sistemas biomédicos
control en lazo cerrado
control PID
control predictivo
modelos fisiológicos
El Texto completo está disponible en PDF
Referencias
[Argoud et al., 1987]
G.M. Argoud, D.S. Schade, R.P. Eaton.
Insulin suppresses its own secretion in vivo.
Diabetes, 36 (1987), pp. 959-962
[Arleth et al., 2000]
T. Arleth, S. Andreassen, M.O. Federici, M.M. Benedetti.
A model of the endogenous glucose balance incorporating the characteristics of glucose transporters.
Comput Methods Programs Biomed, 62 (2000), pp. 219-234
[Atlas et al., 2010]
E. Atlas, R. Nimri, S. Miller, E.A. Gurmberg, M. Phillip.
MD-Logic artificial pancreas system: A pilot study in adults with type 1 diabetes mellitus.
Diabetes Care, (2010),
[Bailey et al., 2009]
T.S. Bailey, H. Zisser, A. Chang.
New features and performance of a next-generation SEVEN-day continuous glucose monitoring system with short lag time.
Diab Technol Ther, 11 (2009), pp. 749-755
[Basu et al., 2003]
R. Basu, B. Di Camillo, G. Toffolo, A. Basu, P. Shah, A. Vella, R. Rizza, C. Cobelli.
Use of a novel triple-tracer approach to assess postprandial glucose metabolism.
Am J Physiol Endocrinol Metab, 284 (2003), pp. E55-E69
[Bequette, 2005]
B.W. Bequette.
A critical assessment of algorithms and challenges in the development of a closed-loop artificial pancreas.
Diab Technol Ther, 7 (2005), pp. 28-47
[Bergman, 2003]
R.N. Bergman.
The minimal model of glucose regulation: a biography.
Adv Exp Med Biol, 537 (2003), pp. 1-19
[Bevier et al., 2008]
W.C. Bevier, H.C. Zisser, L. Jovanovič, D.A. Finan, C.C. Palerm, D.E. Seborg, F.J. Doyle III.
Use of continuous glucose monitoring to estimate insulin requirements in patients with type 1 diabetes mellitus during a short course of prednisone.
J Diabetes Sci Technol, 2 (2008), pp. 578-583
[Bliss, 2007]
Bliss, M. (2007). The discovery of insulin. 25th anniversary ed. The University of Chicago Press.
[Bruttamesso et al., 2009]
D. Bruttamesso, A. Farret, S. Costa, M.C. Marescotti, M. Vettone, A. Avogaro, A. Tiengo, C. Dalla Man, J. Place, A. Fachinetti, S. Guerra, L. Magni, G. de Nicolao, C. Cobelli, E. Renard, A. Maran.
Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: Preliminary studies in Padova and Montpellier.
J Diabetes Sci Technol, 3 (2009), pp. 1014-1021
[Campos-Delgado et al., 2006]
D.U. Campos-Delgado, M. Hernandez-Ordoñez, R. Fermat, A. Gordillo-Moscoso.
Fuzzy-based controller for glucose regulation in type-1 diabetic patients by subcutaneous route.
IEEE Trans Biomed Eng, 53 (2006), pp. 2201-2210
[Caumo et al., 2000]
A. Caumo, R.N. Bergman, C. Cobelli.
Insulin sensitivity from meal tolerance tests in normal subjects: a minimal model index.
J Clin Endocrinol Metab, 85 (2000), pp. 4396-4402
[Chassin et al., 2004]
L.J. Chassin, M.E. Wilinska, R. Hovorka.
Evaluation of glucose controllers in virtual environment: methodology and sample application.
Artif Intell Med, 32 (2004), pp. 171-181
[Clarke et al., 2005]
W.L. Clarke, S. Anderson, L. Farhy, M. Breton, L. Gonder- Frederick, D. Cox, B. Kovatchev.
Evaluating the clinical accuracy of two continuous glucose sensors using continuous glucose-error grid analysis.
Diabetes Care, 28 (2005), pp. 2412-2417
[Clarke et al., 2009]
W.L. Clarke, S. Anderson, M. Breton, S. Patek, L. Kashmer, B. Kovatchev.
Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: The Virginia experience.
J Diabetes Sci Technol, 3 (2009), pp. 1031-1038
[Clemens et al., 1977]
A.H. Clemens, P.H. Chang, R.W. Myers.
The development of Biostator, a glucose controlled insulin infusion system (GCIIS).
Horm Metab Res, S7 (1977), pp. 23-33
[Cryer, 2002]
P.E. Cryer.
Hypoglycemia: the limiting factor in the glycaemic management of type I and type II diabetes.
Diabetologia, 45 (2002), pp. 937-948
[Dalla Man et al., 2006]
C. Dalla Man, M. Camilleri, C. Cobelli.
A system model of oral glucose absorption: Validation on gold standard data.
IEEE Trans Biomed Eng, 53 (2006), pp. 2472-2478
[Dalla Man et al., 2009]
C. Dalla Man, M.D. Breton, C. Cobelli.
Physical activity into the meal glucose-insulin model of type 1 diabetes: in silico studies.
J Diabetes Sci Technol, 3 (2009), pp. 56-67
[Dalla Man et al., 2007]
C. Dalla Man, R.A. Rizza, C. Cobelli.
Meal simulation model of the glucose-insulin system.
IEEE Trans Biomed Eng, 54 (2007), pp. 1740-1749
[Dassau et al., 2008]
E. Dassau, H. Zisser, C.C. Palerm, B.A. Buckingham, L. Jovanovič, F.J. Doyle III.
Modular artificial β-cell system: a prototype for clinical research.
J Diabetes Sci Technol, 2 (2008), pp. 863-872
[Dassau et al., 2010]
E. Dassau, H. Zisser, M.W. Percival, B. Grosman, L. Jovanovič, F.J. Doyle III.
Design, validation and clinical evaluation of a fully automated artificial pancreatic B-cell with unannounced meal using MPMPC and IOB.
In: 3rd Int. Conf. on Advanced Technologies & Treatments for Diabetes,
[DCCT Research and Group, 1993]
DCCT Research Group.
The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus.
N Engl J Med, 329 (1993), pp. 977-986
[D Research Group, 1997]
DCCT Research Group.
Hypoglycemia in the Diabetes Control and Complications Trial.
Diabetes, 46 (1997), pp. 271-286
[Doyle et al., 2007]
F.J. Doyle III, L. Jovanovič, D. Seborg.
Glucose control strategies for treating type 1 diabetes mellitus.
J Process Control, 17 (2007), pp. 572-576
[Ellingsen et al., 2009]
C. Ellingsen, E. Dassau, H. Zisser, B. Grosman, M.W. Percival, L. Jovanovič, F.J. Doyle III.
Safety constraints in an artificial pancreatic β-cell: An implementation of model predictive control with insulin on board.
J Diabetes Sci Technol, 3 (2009), pp. 536-544
[Ellis et al., 2008]
S.L. Ellis, T. Bookout, S.K. Garg, M.E. Izuora.
Use of continuous glucose monitoring to improve diabetes mellitus management.
Endocrinol Metab Clin North Am, 36 (2008), pp. 47-68
[Fabietti et al., 2001]
P.G. Fabietti, G. Calabrese, M. Iorio, S. Bistoni, P. Brunetti, E. Sarti, M.M. Benedetti.
A mathematical model describing the glycemic response of diabetic patients to meal and IV infusion of insulin.
Int J Artif Organs, 24 (2001), pp. 736-742
[Fabietti et al., 2006]
P.G. Fabietti, V. Canonico, M.O. Federici, M.M. Benedetti, E. Sarti.
Control oriented model of insulin and glucose dynamics in type 1 diabetics.
Med Biol Eng Comput, 44 (2006), pp. 69-78
[Facchinetti et al., 2010]
A. Facchinetti, G. Sparacino, C. Cobelli.
Modeling the Error of Continuous Glucose Monitoring Sensor Data: Critical Aspects Discussed through Simulation Studies.
J Diabetes Sci Technol, 4 (2010), pp. 4-14
[Fatourechi et al., 2009]
M.M. Fatourechi, Y.C. Kudva, M.H. Murad, M.B. Elamin, C.C. Tabini, V.M. Montori.
Clinical review: Hypoglycemia with intensive insulin therapy: a systematic review and meta-analyses of randomized trials of continuous subcutaneous insulin infusion versus multiple daily injections.
J Clin Endocrinol Metab, 94 (2009), pp. 729-740
[(2002).,2002]
FDA (2002). General principles of software validation; final guidance for industry and FDA staff. URL: http://www.fda.gov/cdrh/comp/guidance/938.html.
[FDA: Food et al.,2010]
FDA: Food & Drug Administration (n.d.). http://fda.gov. Accessed on March 8, 2010.
[IDF-Europe, 2008]
FEND and IDF-Europe (2008). Diabetes. The Policy Puzzle: Is Europe Making Progress? 2nd edition. URL: http://www.fend.org/
[Garcia-Gabin et al., 2008]
Garcia-Gabin, W., J. Vehi, J. Bondia, C. Tarin and R. Calm (2008). Robust sliding mode closed-loop glucose control with meal compensation in type 1 diabetes mellitus. In: 17th IFAC World Congress.
[Gillis et al., 2007]
R. Gillis, C.C. Palerm, H. Zisser, L. Jovanovič, D. Seborg, F.J. Doyle III.
Glucose estimation and prediction through meal resposes using ambulatory subject data for advisory mode model predicitve control.
J Diabetes Sci Technol, 1 (2007), pp. 825-833
[Gin et al., 2003]
H. Gin, E. Renard, V. Melki, S. Boivin, P. Schaepelynck-Bélicar, B. Guerci, J.L. Selam, J.M. Brun, J.P. Riveline, B. Estour, B.Catargi and EVADIAC Study Group.
Combined improvements in implantable pump technology and insulin stability allow safe and effective long term intraperitoneal insulin delivery in type 1 diabetic patients: the EVADIAC experience.
Diabetes Metab, 29 (2003), pp. 602-607
[Guilhem et al., 2006]
I. Guilhem, A.M. Leguerrier, F. Lecordier, J.Y. Poirier, D. Maugendre.
Technical risks with subcutaneous insulin infusion.
Diabetes Metab, 32 (2006), pp. 279-284
[Guyton et al., 1978]
J.R. Guyton, R.O. Foster, J.S. Soeldner, M.H. Tan, C.B. Kahn, L. Koncz, R.E. Gleason.
A model of glucoseinsulin homeostasis in man that incorporates the heterogeneous fast pool theory of pancreatic insulin relesase.
Diabetes, 27 (1978), pp. 1027-1042
[Herman and Eastman, 1998]
W.H. Herman, R.C. Eastman.
The effects of treatment on the direct costs of diabetes.
Diabetes Care, 21 (1998), pp. C19-C24
[Herrero et al., 2008]
Herrero, P., J. Vehí, R. Corcoy, A. Chico, B. Pons and A. de Leiva (2008). Model based fault detection in the artificial β-cell framework. In: Eighth Diabetes Technology Meeting.
[Sakai (2009)]
M. Hoshino, Y. Haraguchi, I. Mizushima, M. Sakai.
Recent progress in mechanical artificial pancreas.
J Artif Organs, 12 (2009), pp. 141-149
[Hovorka, 2006]
R. Hovorka.
Continuous glucose monitoring and closed-loop systems.
Diabet Med, 23 (2006), pp. 1-12
[Hovorka, 2008]
R. Hovorka.
The future of continuous glucose monitoring: closed loop.
Curr Diabetes Rev, 4 (2008), pp. 269-279
[Hovorka et al., 2002]
R. Hovorka, F. Shojaee-Moradie, P.V. Carroll, L.J. Chassin, I.J. Gowrie, N.C. Jackson, R.S. Tudor, A.M. Umpleby, R.H. Jones.
Partitioning glucose distribution/transport, disposal, and endogenous production during IVGTT.
Am J Physiol Endocrinol Metab, 282 (2002), pp. E992-E1007
[Hovorka et al., 2010]
R. Hovorka, J.M. Allen, D. Elleri, L.J. Chassin, J. Harris, D. Xing, C. Kollman, T. Hovorka, A.M. Larsen, M. Nodale, A. De Palma, M.E. Wilinska, C.L. Acerini, D.B. Dunger.
Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial.
Lancet, 375 (2010), pp. 743-751
[Hovorka et al., 2004]
R. Hovorka, V. Canonico, L.J. Chassin, U. Haueter, M. Massi- Benedetti, M.O. Federici, T.R. Pieber, H.C. Schaller, L. Schaupp, T. Vering, M.E. Wilinska.
Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes.
Physiol Meas, 25 (2004), pp. 905-920
[Ibbini and Massadeh, 2004]
M. Ibbini, M.A. Massadeh.
A fuzzy logic based closed-loop control system for the blood glucose level regulation in diabetes.
J Med Eng Tech, 29 (2004), pp. 64-69
[Insel et al., 1974]
P.A. Insel, K.J. Kramer, R.S. Sherwin, J.E. Liljenquist, J.D. Tobin, R. Andres, M. Berman.
Modeling the insulin-glucose system in man.
Fed Proc, 33 (1974), pp. 1865-1868
[JDRF, 2010]
JDRF: Artificial Pancreas Project (n.d.).http://jdrf.org. Accessed on March 8 2010.
[Jeitler et al., 2008]
K. Jeitler, K. Horvath, A. Berghold, T.W. Gratzer, K. Neeser, T.R. Pieber, A. Siebenhofer.
Continuous subcutaneous insulin infusion versus multiple daily insulin injections in patients with diabetes mellitus: systematic review and meta-analysis.
Diabetologia, 51 (2008), pp. 941-951
[Jönsson, 1998]
B. Jönsson.
The economic impact of diabetes.
Diabetes Care, 21 (1998), pp. C7-C10
[Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group, 2008]
Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group.
Continuous glucose monitoring and intensive treatment of type 1 diabetes.
N Engl J Med, 359 (2008), pp. 1464-1476
[Kanderian et al., 2006]
S. Kanderian, M.F. Saad, K. Rebrin, G.M. Steil.
Modeling glucose profiles obtained using closed loop insulin delivery – I mplications for controller optimization.
Diabetes, 55 (2006), pp. A98
[Kanderian et al., 2009]
S. Kanderian, S. Weinzimer, G. Voskanyan, G.M. Steil.
Identification of Intraday Metabolic Profiles during Closed-Loop Glucose Control in Individuals with Type 1 Diabetes.
J Diabetes Sci Technol, 3 (2009), pp. 1047-1057
[Keenan et al., 2010]
D.B. Keenan, R. Cartaya, J.J. Mastrototaro.
Accuracy of a new real-time continuous glucose monitoring algorithm.
J Diabetes Sci Technol, 4 (2010), pp. 111-118
[King et al., 2007]
C. King, S.M. Anderson, M. Breton, W.L. Clarke, B.P. Kovatchev.
Modeling of calibration effectiveness and blood-to-interstitial glucose dynamics as potential confounders of the accuracy of continuous glucose sensors during hyperinsulinemic clamp.
J Diabetes Sci Technol, 1 (2007), pp. 317-322
[Klonoff and Schwartz, 2000]
D.C. Klonoff, D.M. Schwartz.
An economic analysis of interventions for diabetes.
Diabetes Care, 23 (2000), pp. 390-404
[Klonoff and Reyes, 2009]
D.C. Klonoff, J.S. Reyes.
Insulin pump safety meeting: Summary report.
J Diabetes Sci Technol, 3 (2009), pp. 396-402
[Koenig et al., 1976]
R.J. Koenig, C.M. Peterson, R.L. Jones, C. Saudek, M. Lehrman, A. Cerami.
Correlation of glucose regulation and hemoglobin A1c in diabetes mellitus.
N Engl J Med, 295 (1976), pp. 417-420
[Kovatchev et al., 2008]
B. Kovatchev, S. Anderson, L. Heinemann, W.L. Clarke.
Comparison of the numerical and clinical accuracy of four continuous glucose monitors.
Diabetes Care, 31 (2008), pp. 1160-1164
[Kovatchev et al., 2009a]
B. Kovatchev, S. Patek, E. Dassau, F.J. Doyle III, L. Magni, G. de Nicolao, C. Cobelli.
Control to range for diabetes: Functionality and modular architecture.
J Diabetes Sci Technol, 3 (2009), pp. 1058-1065
[Kovatchev et al., 2009b]
B.P. Kovatchev, M. Breton, C. Dalla Man, C. Cobelli.
In Silico Preclinical Trials: A Proof of Concept in Closed-Loop Control of Type 1 Diabetes.
J Diabetes Sci Technol, 3 (2009), pp. 44-55
[Kowalski, 2009]
A. Kowalski.
Can we really close the loop and how soon? Accelerating the availability of an artificial pancreas: a roadmap to better diabetes outcomes.
Diab Technol Ther, 11 (2009), pp. S113-S119
[Kumareswaran et al., 2009]
K. Kumareswaran, M.L. Evans, R. Hovorka.
Artificial pancreas: an emerging approach to treat type 1 diabetes.
Expert Rev Med Devices, 6 (2009), pp. 401-410
[Leal et al., 2010]
Y. Leal, W. García-Gabín, J. Bondia, E. Esteve, W. Ricart, J.M. Fernández-Real, J. Vehí.
Real-time glucose estimation algorithm for continuous glucose monitoring using autoregressive models.
J Diabetes Sci Technol, 4 (2010), pp. 391-403
[Lee et al., 2009]
H. Lee, B.A. Buckingham, D.M. Wilson, B.W. Bequette.
A closed-loop artificial pancreas using model predictive control and meal size estimator.
J Diabetes Sci Technol, 3 (2009), pp. 1082-1090
[Lee and Hitt. In press]
Lee, S. and E. Hitt (n.d.). Continuous subcutaneous insulin infusion: Intensive treatment, flexible lifestyle. http://cme.medscape.com/viewarticle/460365.
[Lehmann et al., 1994]
E.D. Lehmann, T. Deutsch, E.R. Carson, P.H. Söksen.
AIDA: an interactive diabetes advisor.
Comput Methods Programs Biomed, 41 (1994), pp. 183-203
[Lynch and Bequette, 2002]
S.M. Lynch, B.W. Bequette.
Model predictive control of blood glucose in type 1 diabetics using subcutaneous glucose measurements.
Proceeding of the American Control Conference, (2002), pp. 4039-4043
[Magni et al., 2007]
L. Magni, D.M. Raimondo, L. Bossi, C. Dalla Man, G. De Nicolao, B. Kovatchev, C. Cobelli.
Model predictive control of type 1 diabetes: an in silico trial.
J Diabetes Sci Technol, 1 (2007), pp. 804-812
[Mazze et al., 2009]
R.S. Mazze, E. Strock, S. Borgman, D. Wesley, P. Stout, J. Racchini.
Evaluating the accuracy, reliability, and clinical applicability of continuous glucose monitoring (CGM): is CGM ready for real time?.
Diab Technol Ther, 11 (2009), pp. 11-18
[McMahon et al., 2007]
S.K. McMahon, L.D. Ferreira, N. Ratnam, R.J. Davey, L.M. Youngs, E.A. Davis, P.A. Fournier, T.W. Jones.
Glucose requirements to maintain euglycemia after moderate-intensity afternoon exercise in adolescents with type 1 diabetes are increased in a biphasic manner.
J Clin Endocrinol Metab, 92 (2007), pp. 963-968
[Mecklenburg et al., 1986]
R.S. Mecklenburg, T.S. Guinn, C.A. Sannar, B.A. Blumenstein.
Malfunction of continuous subcutaneous insulin infusion systems: a one-year prospective study of 127 patients.
Diabetes Care, 9 (1986), pp. 351-355
[Mendosa, In press]
Mendosa, D. (n.d.). Meter memories: how Tom, Dick, and Charlie did it. http://www.mendosa.com/memories.htm.
[Menzin et al., 2001]
J. Menzin, C. Langley-Hawthorne, M. Friedman, L. Boulanger, R. Cavanaugh.
Potential short-term economic benefits of improved glycemic control.
Diabetes Care, 24 (2001), pp. 51-55
[Monsod et al., 2002]
T.P. Monsod, D.E. Flanagan, F. Rife, R. Saenz, S. Caprio, R.S. Sherwin, W.V. Tamborlane.
Do sensor glucose levels accurately predict plasma glucose concentrations during hypoglycemia and hyperinsulinemia?.
Diabetes Care, 25 (2002), pp. 889-893
[Mudaliar et al., 1999]
S.R. Mudaliar, F.A. Lindberg, M. Joyce, P. Beerdsen, P. Strange, A. Lin, R.R. Henry.
Insulin aspart (B28 asp-insulin): a fast-acting analog of human insulin: absorption kinetics and action profile compared with regular human insulin in healthy nondiabetic subjects.
Diabetes Care, 22 (1999), pp. 1501-1506
[Nilsson et al., 2006]
A. Nilsson, Y. Granfeldt, E. Östman, T. Preston, I. Björck.
Effects of GI and content of indigestible carbohydrates of cereal-based evening meals on glucose tolerance at a subsequent standardised breakfast.
Eur J Clin Nutr, 60 (2006), pp. 1092-1099
[Oliver et al., 2009a]
N. Oliver, P. Georgiou, D. Johnston, C. Toumazou.
A benchtop closed-loop system controlled by a bio-inspired silicon implementation of the pancreatic beta cell.
J Diabetes Sci Technol, 3 (2009), pp. 1419-1424
[Oliver et al., 2009b]
N.S. Oliver, C. Toumazou, A.E.G. Cass, D.G. Johnston.
Glucose sensors: a review of current and emerging technology.
Diabet Med, 26 (2009), pp. 197-210
[Omnipod Insulin Pump, 2010]
Omnipod Insulin Pump (n.d.). http://www.myomnipod.com/.Accessed on March 13, 2010.
[Palerm et al., 2007]
C.C. Palerm, H. Zisser, W.C. Bevier, L. Jovanovič, F.J. Doyle III.
Prandial insulin dosing using run-to-run control: application of clinical data and medical expertise to define a suitable performance metric.
Diabetes Care, 30 (2007), pp. 1131-1136
[Palerm et al., 2008]
C.C. Palerm, N. Kurtz, S. Paz, D.B. Keenan, G.M. Steil, F.R. Kandeel.
Closed-loop insulin delivery utilizing insulin feedback: preliminary clinical results.
In: Eighth Annual Diabetes Technology Meeting, pp. S44
[Parker et al., 1999]
R.S. Parker, F.J. Doyle III, N.A. Peppas.
A modelbased algorithm for blood glucose control in type i diabetic patients.
IEEE Trans Biomed Eng, 46 (1999), pp. 148-157
[Parker et al., 2000]
R.S. Parker, F.J. Doyle III, J.H. Ward, N.A. Peppas.
Robust H∞ glucose control in diabetes using a physiological model.
AIChE Journal, 46 (2000), pp. 2537-2549
[Patek et al., 2009]
S.D. Patek, B.W. Bequette, M. Breton, B.A. Buckingham, E. Dassau, F.J. Doyle III, J. Lum, L. Magni, H. Zisser.
In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus.
J Diabetes Sci Technol, 3 (2009), pp. 269-282
[Percival et al., 2008]
M.W. Percival, E. Dassau, H. Zisser, L. Jovanovič, F.J. Doyle III.
Closed-loop control of an artificial pancreatic beta cell using multi-parametric model predictive control.
AIChe Conference, (2008),
[Pickup and Keen, 2002]
J. Pickup, H. Keen.
Continuous subcutaneous insulin infusion at 25 years: evidence base for the expanding use of insulin pump therapy in type 1 diabetes.
Diabetes Care, 25 (2002), pp. 593-598
[Pinkos et al., 2007]
A. Pinkos, G. Arreaza-Rubin, W. Heetderks, I. Irony, H. Joffe, B. Schneider, C. Zimliki.
FDA's proactive role in the development of an artificial pancreas for the treatment of diabetes mellitus.
Drug Discov Today Technol, 4 (2007), pp. 25-28
[Quesada et al., 2008]
I. Quesada, E. Tuduri, C. Ripoll, A. Ñadal.
Physiology of the pancreatic α-cell and glucagon secretion: role in glucose homeostasis and diabetes.
J Endocrinol, 199 (2008), pp. 5-19
[Quiro z and Femat, 2010]
G. Quiro z, R. Femat.
Theoretical blood glucose control in hyper- and hypoglycemic and exercise scenarios by means of an h1 algorithm.
J Theor Biol, 263 (2010), pp. 154-160
[Rebrin and Steil, 2000]
K. Rebrin, G.M. Steil.
Can interstitial glucose assessment replace blood glucose measurements?.
Diab Technol Ther, 2 (2000), pp. 461-472
[Rebrin et al., 1999]
K. Rebrin, G.M. Steil, W.P. van Antwerp, J.J. Mastrototaro.
Subcutaneous glucose predicts plasma glucose independent of insulin: implications for continuous monitoring.
Am J Physiol Endocrinol Metab, 277 (1999), pp. E561-E571
[Renard, 2008]
E. Renard.
Implantable continuous glucose sensors.
Curr Diabetes Rev, 4 (2008), pp. 169-174
[Renard et al., 2006]
E. Renard, G. Costalat, H. Chevassus, J. Bringer.
Artificial beta-cell: clinical experience toward an implantable closed-loop insulin delivery system.
Diabetes Metab, 32 (2006), pp. 497-502
[Renard et al., 2010]
E. Renard, J. Place, M. Cantwell, H. Chevassus, C.C. Palerm.
Closed-loop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas.
Diabetes Care, 33 (2010), pp. 121-127
[Renard, 2007]
E.P. Renard, Schaepelynck-Belicar and EVADIAC Group.
Implantable insulin pumps. A position statement. about their clinical use.
Diabetes Metab, 33 (2007), pp. 158-166
[Rendell, 2008]
M. Rendell.
Insulin: moments in history.
Drug Dev Res, 69 (2008), pp. 95-100
[Roglic and Unwin, 2010]
G. Roglic, N. Unwin.
Mortality attributable to diabetes: Estimates for the year 2010.
Diabetes Res Clin Pract, 87 (2010), pp. 15-19
[Ruiz-Velázquez et al., 2004]
E. Ruiz-Velázquez, R. Femat, D.U. Campos-Delgado.
Blood glucose control for type i diabetes mellitus: A robust tracking h∞ problem.
Control Eng Pract, 12 (2004), pp. 1179-1195
[Shaller et al., 2006]
H.C. Shaller, L. Schaupp, M. Bodenlenz, M.E. Willinska, L.J. Chassin, P. Wach, T. Vering, R. Hovorka, T.R. Pieber.
On-line adaptive algorithm with glucose prediction capacity for subcutaneous closed loo control of glucose: evaluation under fasting conditions in patients with type 1 diabetes.
Diabet Med, 23 (2006), pp. 90-93
[Shaw et al., 2010]
J.E. Shaw, R.A. Sicree, P.Z. Zimmet.
Global estimates of the prevalence of diabetes for 2010 and 2030.
Diabetes Res Clin Pract, 87 (2010), pp. 4-14
[Sherr et al., 2009]
J.L. Sherr, C.C. Palerm, E. Cengiz, B. Clark, N. Kurtz, M. Loutseiko, A. Roy, L. Carria, W.V. Tamborlane, S.A. Weinzimer.
Frequency of exercise related hypoglycemia using a closed-loop artificial pancreas: Preliminary results.
Ninth Annual Diabetes Technology Meeting,
[Singh-Franco et al., 2007]
D. Singh-Franco, G. Robles, D. Gazze.
Pramlintide acetate injection for the treatment of type 1 and type 2 diabetes mellitus.
Clin Ther, 29 (2007), pp. 535-562
[Sorensen, 1985]
Sorensen, J.T. (1985). A physiologic model of glucose metabolism in man and its use to design and assess improved insulin therapies for diabetes. PhD thesis. Massachusetts Institute of Technology.
[Steil et al., 2004]
G.M. Steil, A.E. Panteleon, K. Rebrin.
Closed-loop insulin delivery—the path to physiological glucose control.
Adv Drug Deliv Rev, 56 (2004), pp. 125-144
[Steil et al., 2006]
G.M. Steil, K. Rebrin, C. Darwin, F. Hariri, M.F. Saad.
Feasibility of automating insulin delivery for the treatment of type 1 diabetes.
Diabetes, 55 (2006), pp. 3344-3350
[Steil et al., 2003]
G.M. Steil, K. Rebrin, R. Janowski, C. Darwin, M.F. Saad.
Modeling β-cell insulin secretion — implications for closed-loop glucose homeostasis.
Diabetes Technol Ther, 5 (2003), pp. 953-964
[Sternberg et al., 1996]
F. Sternberg, C. Meyerhoff, F.J. Mennel, H. Mayer, F. Bischof, E.F. Pfeiffer.
Does fall in tissue glucose precede fall in blood glucose?.
Diabetologia, 39 (1996), pp. 609-612
[Takahashi et al., 2008]
D. Takahashi, Y. Xiao, F. Hu.
A survey of insulin dependent diabetes part II: Control methods.
Int J Telemed Appl, (2008),
[Trajanoski and Wach, 1998]
Z. Trajanoski, P. Wach.
Neural predictive controller for insulin delivery using the subcutaneous route.
IEEE Trans Biomed Eng, 45 (1998), pp. 1122-1134
[Prospective Diabetes Study Group, 1998]
U.K. Prospective Diabetes Study Group (1998).
Intensive bloodglucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33).
Lancet, 352 (1998), pp. 837-853
[Waldhäusl, 1989]
W. Waldhäusl.
Circadian rhythms of insulin needs and actions.
Diabetes Res Clin Pract, 6 (1989), pp. S17-S24
[Wang, 2008]
J. Wang.
Electrochemical glucose biosensors.
Chem Rev, 108 (2008), pp. 814-825
[Wang et al., 2010]
Y. Wang, E. Dassau, F.J. Doyle III.
Closed-loop control of artificial pancreatic β-cell in type 1 diabetes mellitus using model predictive iterative learning control.
IEEE Trans Biomed Eng, 57 (2010), pp. 211-219
[Weinstein et al., 2007]
R.L. Weinstein, S.L. Schwartz, R.L. Brazg, J.R. Bugler, T.A. Peyser, G.V. McGarraugh.
Accuracy of the 5-day FreeStyle Navigator continuous glucose monitoring system: comparison with frequent laboratory reference measurements.
Diabetes Care, 30 (2007), pp. 1125-1130
[Weinzimer et al., 2008]
S.A. Weinzimer, G.M. Steil, K.L. Swan, J. Dziura, N. Kurtz, W.V. Tamborlane.
Fully automated closed-loop insulin delivery vs. semi-automated hybrid control in pediatric patients with type 1 diabetes using an artificial pancreas.
Diabetes Care, 31 (2008), pp. 934-939
[Wentholt et al., 2005]
I.M. Wentholt, M.A. Vollebregt, A.A. Hart, J.B. Hoekstra, J.H. DeVries.
Comparison of a needle-type and a microdialysis continuous glucose monitor in type 1 diabetic patients.
Diabetes Care, 28 (2005), pp. 2871-2876
[Wilinska and Hovorka, 2008]
M.E. Wilinska, R. Hovorka.
Simulation models for in silico testing of closed-loop glucose controllers in type 1 diabetes.
Drug Discov Today Dis Models, 5 (2008), pp. 289-298
[Wilinska et al., 2010]
M.E. Wilinska, L.J. Chassin, C.L. Acerini, J.M. Allen, D.B. Dunger, R. Hovorka.
Simulation environment to evaluate closed-loop insulin delivery systems in type 1 diabetes.
J Diabetes Sci Technol, 4 (2010), pp. 132-144
[Wilinska et al., 2005]
M.E. Wilinska, L.J. Chassin, H.C. Schaller, L. Schaupp, T.R. Pieber, R. Hovorka.
Insulin kinetics in type-1 diabetes: continuous and bolus delivery of rapid acting insulin.
IEEE Trans Biomed Eng, 52 (2005), pp. 3-12
[Zheng et al., 2007]
Y. Zheng, H.T. Kreuwel, D.L. Young, L.K. Shoda, S. Ramanujan, K.G. Gadkar, M.A. Atkinson, C.C. Whiting.
The virtual NOD mouse: applying predictive biosimulation to research in type 1 diabetes.
Ann N Y Acad Sci, 1103 (2007), pp. 45-62
[Zisser et al., 2009a]
H. Zisser, C.C. Palerm, W.C. Bevier, F.J. Doyle III, L. Jovanovič.
Clinical update on optimal prandial insulin dosing using a refined run-to-run control algorithm.
J Diabetes Sci Technol, 3 (2009), pp. 487-491
[Zisser et al., 2008]
H. Zisser, L. Robinson, W. Bevier, E. Dassau, C. Ellingsen, C.F.J. Doyle III, L. Jovanovič.
Bolus calculator: a review of four ‘smart’ insulin pumps.
Diab Technol Ther, 10 (2008), pp. 441-444
[Zisser et al., 2009b]
H. Zisser, T.S. Bailey, S. Schwartz, R.E. Ratner, J. Wise.
Accuracy of the SEVEN continuous glucose monitoring system: comparison with frequently sampled venous glucose measurements.
J Diabetes Sci Technol, 3 (2009), pp. 1146-1154
Copyright © 2010. Elsevier España, S.L.. Todos los derechos reservados